scholarly journals Forward and Inverse Modelling of Atmospheric Nitrous Oxide Using MIROC4-Atmospheric Chemistry-Transport Model

2022 ◽  
Author(s):  
Prabir K. PATRA ◽  
Edward J. DLUGOKENCKY ◽  
James W. ELKINS ◽  
Geoff S. DUTTON ◽  
Yasunori TOHJIMA ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Inverse Modelling ◽  
Chemistry Transport Model

scholarly journals Modelling atmospheric OH-reactivity in a boreal forest ecosystem

2011 ◽  
Vol 11 (18) ◽  
pp. 9709-9719 ◽  
Author(s):  
D. Mogensen ◽  
S. Smolander ◽  
A. Sogachev ◽  
L. Zhou ◽  
V. Sinha ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Inorganic Compounds ◽  
Chemistry Transport Model ◽  
One Dimensional ◽  
Inorganic Species ◽  
Individual Contributions ◽  
The Individual

Abstract. We have modelled the total atmospheric OH-reactivity in a boreal forest and investigated the individual contributions from gas phase inorganic species, isoprene, monoterpenes, and methane along with other important VOCs. Daily and seasonal variation in OH-reactivity for the year 2008 was examined as well as the vertical OH-reactivity profile. We have used SOSA; a one dimensional vertical chemistry-transport model (Boy et al., 2011a) together with measurements from Hyytiälä, SMEAR II station, Southern Finland, conducted in August 2008. Model simulations only account for ~30–50% of the total measured OH sink, and in our opinion, the reason for missing OH-reactivity is due to unmeasured unknown BVOCs, and limitations in our knowledge of atmospheric chemistry including uncertainties in rate constants. Furthermore, we found that the OH-reactivity correlates with both organic and inorganic compounds and increases during summer. The summertime canopy level OH-reactivity peaks during night and the vertical OH-reactivity decreases with height.

scholarly journals Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

2013 ◽  
Vol 13 (19) ◽  
pp. 9917-9937 ◽  
Author(s):  
R. Locatelli ◽  
P. Bousquet ◽  
F. Chevallier ◽  
A. Fortems-Cheney ◽  
S. Szopa ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Initial Conditions ◽  
Spatial Scales ◽  
Global Scale ◽  
Methane Emissions ◽  
Inverse Modelling ◽  
Model Errors ◽  
Inverse Systems ◽  
The Impact

Abstract. A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System) inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure) is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr−1 at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr−1 in North America to 7 Tg yr−1 in Boreal Eurasia (from 23 to 48%, respectively). At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly question the consistency of transport model errors in current inverse systems. Future inversions should include more accurately prescribed observation covariances matrices in order to limit the impact of transport model errors on estimated methane fluxes.

scholarly journals Operational total and tropospheric NO<sub>2</sub> column retrieval for GOME-2

2011 ◽  
Vol 4 (7) ◽  
pp. 1491-1514 ◽  
Author(s):  
P. Valks ◽  
G. Pinardi ◽  
A. Richter ◽  
J.-C. Lambert ◽  
N. Hao ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Chemistry Transport Model ◽  
Air Mass ◽  
Cloud Properties ◽  
The Pacific ◽  
Tropospheric No2 ◽  
Data Processor ◽  
Radiance Data

Abstract. This paper presents the algorithm for the operational near real time retrieval of total and tropospheric NO2 columns from the Global Ozone Monitoring Experiment (GOME-2). The retrieval is performed with the GOME Data Processor (GDP) version 4.4 as used by the EUMETSAT Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF). The differential optical absorption spectroscopy (DOAS) method is used to determine NO2 slant columns from GOME-2 (ir)radiance data in the 425–450 nm range. Initial total NO2 columns are computed using stratospheric air mass factors, and GOME-2 derived cloud properties are used to calculate the air mass factors for scenarios in the presence of clouds. To obtain the stratospheric NO2 component, a spatial filtering approach is used, which is shown to be an improvement on the Pacific reference sector method. Tropospheric air mass factors are computed using monthly averaged NO2 profiles from the MOZART-2 chemistry transport model. An error analysis shows that the random error in the GOME-2 NO2 slant columns is approximately 0.45 × 1015 molec cm−2. As a result of the improved quartz diffuser plate used in the GOME-2 instrument, the systematic error in the slant columns is strongly reduced compared to GOME/ERS-2. The estimated uncertainty in the GOME-2 tropospheric NO2 column for polluted conditions ranges from 40 to 80 %. An end-to-end ground-based validation approach for the GOME-2 NO2 columns is illustrated based on multi-axis MAXDOAS measurements at the Observatoire de Haute Provence (OHP). The GOME-2 stratospheric NO2 columns are found to be in good overall agreement with coincident ground-based measurements at OHP. A time series of the MAXDOAS and the GOME-2 tropospheric NO2 columns shows that pollution episodes at OHP are well captured by GOME-2. Monthly mean tropospheric columns are in very good agreement, with differences generally within 0.5 × 1015 molec cm−2.

scholarly journals Improving the prediction of an atmospheric chemistry transport model using gradient-boosted regression trees

2020 ◽  
Vol 20 (13) ◽  
pp. 8063-8082 ◽  
Author(s):  
Peter D. Ivatt ◽  
Mathew J. Evans
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Mean Square ◽  
Model Bias ◽  
Chemistry Transport Model ◽  
Pearson's R ◽  
Process Based Models

Abstract. Predictions from process-based models of environmental systems are biased, due to uncertainties in their inputs and parameterizations, reducing their utility. We develop a predictor for the bias in tropospheric ozone (O3, a key pollutant) calculated by an atmospheric chemistry transport model (GEOS-Chem), based on outputs from the model and observations of ozone from both the surface (EPA, EMEP, and GAW) and the ozone-sonde networks. We train a gradient-boosted decision tree algorithm (XGBoost) to predict model bias (model divided by observation), with model and observational data for 2010–2015, and then we test the approach using the years 2016–2017. We show that the bias-corrected model performs considerably better than the uncorrected model. The root-mean-square error is reduced from 16.2 to 7.5 ppb, the normalized mean bias is reduced from 0.28 to −0.04, and Pearson's R is increased from 0.48 to 0.84. Comparisons with observations from the NASA ATom flights (which were not included in the training) also show improvements but to a smaller extent, reducing the root-mean-square error (RMSE) from 12.1 to 10.5 ppb, reducing the normalized mean bias (NMB) from 0.08 to 0.06, and increasing Pearson's R from 0.76 to 0.79. We attribute the smaller improvements to the lack of routine observational constraints for much of the remote troposphere. We show that the method is robust to variations in the volume of training data, with approximately a year of data needed to produce useful performance. Data denial experiments (removing observational sites from the algorithm training) show that information from one location (for example Europe) can reduce the model bias over other locations (for example North America) which might provide insights into the processes controlling the model bias. We explore the choice of predictor (bias prediction versus direct prediction) and conclude both may have utility. We conclude that combining machine learning approaches with process-based models may provide a useful tool for improving these models.

scholarly journals What drives the observed variability of HCN in the troposphere and lower stratosphere?

2009 ◽  
Vol 9 (21) ◽  
pp. 8531-8543 ◽  
Author(s):  
Q. Li ◽  
P. I. Palmer ◽  
H. C. Pumphrey ◽  
P. Bernath ◽  
E. Mahieu
Keyword(s):  
Atmospheric Chemistry ◽  
Lower Stratosphere ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Negative Bias ◽  
Mixing Ratio ◽  
Chemistry Transport Model ◽  
Annual Variations ◽  
Surface Emission ◽  
Chemistry Experiment

Abstract. We use the GEOS-Chem global 3-D chemistry transport model to investigate the relative importance of chemical and physical processes that determine observed variability of hydrogen cyanide (HCN) in the troposphere and lower stratosphere. Consequently, we reconcile ground-based FTIR column measurements of HCN, which show annual and semi-annual variations, with recent space-borne measurements of HCN mixing ratio in the tropical lower stratosphere, which show a large two-year variation. We find that the observed column variability over the ground-based stations is determined by a superposition of HCN from several regional burning sources, with GEOS-Chem reproducing these column data with a positive bias of 5%. GEOS-Chem reproduces the observed HCN mixing ratio from the Microwave Limb Sounder and the Atmospheric Chemistry Experiment satellite instruments with a mean negative bias of 20%, and the observed HCN variability with a mean negative bias of 7%. We show that tropical biomass burning emissions explain most of the observed HCN variations in the upper troposphere and lower stratosphere (UTLS), with the remainder due to atmospheric transport and HCN chemistry. In the mid and upper stratosphere, atmospheric dynamics progressively exerts more influence on HCN variations. The extent of temporal overlap between African and other continental burning seasons is key in establishing the apparent bienniel cycle in the UTLS. Similar analysis of other, shorter-lived trace gases have not observed the transition between annual and bienniel cycles in the UTLS probably because the signal of inter-annual variations from surface emission has been diluted before arriving at the lower stratosphere (LS), due to shorter atmospheric lifetimes.

scholarly journals Impact of reactive bromine chemistry in the troposphere

2004 ◽  
Vol 4 (11/12) ◽  
pp. 2481-2497 ◽  
Author(s):  
R. von Glasow ◽  
R. von Kuhlmann ◽  
M. G. Lawrence ◽  
U. Platt ◽  
P. J. Crutzen
Keyword(s):  
Atmospheric Chemistry ◽  
Dimethyl Sulfide ◽  
Marine Boundary Layer ◽  
Transport Model ◽  
Sea Salt ◽  
Chemistry Transport Model ◽  
Bromine Oxide ◽  
Mixing Ratios ◽  
Sea Salt Aerosol ◽  
Field Campaigns

Abstract. Recently several field campaigns and satellite observations have found strong indications for the presence of bromine oxide (BrO) in the free troposphere. Using a global atmospheric chemistry transport model we show that BrO mixing ratios of a few tenths to 2 pmol mol-1 lead to a reduction in the zonal mean O3 mixing ratio of up to 18% in widespread areas and regionally up to 40% compared to a model run without bromine chemistry. A lower limit approach for the marine boundary layer, that does not explicitly include the release of halogens from sea salt aerosol, shows that for dimethyl sulfide (DMS) the effect is even larger, with up to 60% reduction of its tropospheric column. This is accompanied by dramatic changes in DMS oxidation pathways, reducing its cooling effect on climate. In addition there are changes in the HO2:OH ratio that also affect NOx and PAN. These results imply that potentially significant strong sinks for O3 and DMS have so far been ignored in many studies of the chemistry of the troposphere.

scholarly journals Three-dimensional model evaluation of the Ozone Depletion Potentials for n-propyl bromide, trichloroethylene and perchloroethylene

2011 ◽  
Vol 11 (5) ◽  
pp. 2371-2380 ◽  
Author(s):  
D. J. Wuebbles ◽  
K. O. Patten ◽  
D. Wang ◽  
D. Youn ◽  
M. Martínez-Avilés ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Ozone Depletion ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Three Dimensional ◽  
Past Study ◽  
Three Dimensional Model ◽  
Chemistry Transport Model ◽  
Land Surfaces ◽  
Simplified Modeling

Abstract. The existing solvents trichloroethylene (TCE) and perchloroethylene (PCE) and proposed solvent n-propyl bromide (nPB) have atmospheric lifetimes from days to a few months, but contain chlorine or bromine that could affect stratospheric ozone. Several previous studies estimated the Ozone Depletion Potentials (ODPs) for various assumptions of nPB emissions location, but these studies used simplified modeling treatments. The primary purpose of this study is to reevaluate the ODP for n-propyl bromide (nPB) using a current-generation chemistry-transport model of the troposphere and stratosphere. For the first time, ODPs for TCE and PCE are also evaluated in a three-dimensional, global atmospheric chemistry-transport model. Emissions representing industrial use of each compound are incorporated on land surfaces from 30° N to 60° N. The atmospheric chemical lifetime obtained for nPB is 24.7 days, similar to past literature, but the ODP is 0.0049, lower than in our past study of nPB. The derived atmospheric lifetime for TCE is 13.0 days and for PCE is 111 days. The corresponding ODPs are 0.00037 and 0.0050, respectively.

scholarly journals Air-to-sea flux of soluble iron: is it driven more by HNO<sub>3</sub> or SO<sub>2</sub>? – an examination in the light of dust aging

2007 ◽  
Vol 7 (4) ◽  
pp. 10043-10063 ◽  
Author(s):  
H. Yang ◽  
Y. Gao
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
World Ocean ◽  
Global Ocean ◽  
Relative Role ◽  
Chemistry Transport Model ◽  
Acidic Gases ◽  
Relative Contribution ◽  
The World

Abstract. Aeolian dust provides the major micronutrient of soluble Fe to organisms in certain regions of the global ocean. In this study, we conduct numerical experiments using the MOZART-2 atmospheric chemistry transport model to simulate the global distribution of soluble Fe flux and Fe solubility. One of the mechanisms behind the hypothesis of acid mobilization of Fe in the atmosphere is that the coating of acidic gases changes dust from hydrophobic to hydrophilic, a prerequisite of Fe mobilization. We therefore include HNO3, SO2 and sulfate (SO42−) as dust transformation agents in the model. General agreement in Fe solubility within a factor of 2 is achieved between model and observations. The total flux of soluble Fe to the world ocean is estimated to be 731–924×109 g yr−1, and the average Fe solubility is 6.4–8.0%. Wet deposition contributes over 80% to total soluble Fe flux to most of the world oceans. Special attention is paid to the relative role of HNO3 versus SO2 and sulfate. We demonstrate that coating by HNO3 produces over 36% of soluble Fe fluxes compared to that by SO2 and sulfate combined in every major oceanic basin. Given present trends in the emissions of NOx and SO2, the relative contribution of HNO3 to Fe mobilization may get even larger in the future.

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